We benchmark the cameras by executing different custom CNN models and standardized of-the-shelf deep learning architecture. In the first benchmark, we use a CNN model generator which generates a range of CNN models with varying number of parameters while in the second benchmark we use two standardized deep learning models MobileNet[1]} and YOLO[2]}. For each experiment, the models perform inference on-board and two different performance metrics are recorded: latency and throughput. Fig REF  shows the distribution of all individual experiments with respect to the number of parameters.
